Image Generation MCP Server

@sarthakkimtani

Repository

Basic information

About Image Generation MCP Server

MCP server enabling Image Generation for LLMs, built in Python and integrated with Together AI.

#python #ai #mcp #llms #claude-ai

Image Generation MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "image-gen": {
      "command": "uv",
      "args": [
        "--directory",
        "/ABSOLUTE/PATH/TO/image-gen/",
        "run",
        "image-gen"
      ],
      "env": {
        "TOGETHER_AI_API_KEY": "<API KEY>"
      }
    }
  }
}

Image Generation MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Image Generation MCP Server?

A Model Context Protocol (MCP) server that enables seamless generation of high-quality images via Together AI. It provides a standardized interface to specify image generation parameters for MCP-compatible clients.

How to use Image Generation MCP Server?

Install using uv and configure in your MCP client (e.g., Claude Desktop) by adding a server entry with the command uv --directory /ABSOLUTE/PATH/TO/image-gen/ run image-gen and the required TOGETHER_AI_API_KEY environment variable. Once connected, call the generate_image tool with a descriptive prompt and optional width, height, and model parameters.

Key features of Image Generation MCP Server

High-quality image generation via the Flux.1 Schnell model
Customizable output dimensions (width and height)
Clear error handling for prompt validation and API issues
Easy integration with MCP-compatible clients
Support for specifying an exact Together AI model with automatic fallback

Use cases of Image Generation MCP Server

Generate images from descriptive text prompts for content creation
Specify custom dimensions to match project layout requirements
Integrate image generation into existing MCP-based workflows and tools

Frequently asked questions

What model does the server use by default?

The default model is `black-forest-labs/FLUX.1-schnell`. You can override it with any Together AI model name via the `model` parameter.

What are the prerequisites for running the server?

You need Python 3.12 or higher, the `httpx` and `mcp` packages, and a valid Together AI API key.

How do I configure the API key?

Set the `TOGETHER_AI_API_KEY` environment variable in your MCP client configuration (e.g., `claude_desktop_config.json`).

What tools does the server provide?

It provides one tool: `generate_image`, which accepts a `prompt` (required), and optional `width`, `height`, and `model` parameters.

Can I specify the image dimensions?

Yes, you can optionally set `width` and `height` in pixels when calling `generate_image`.

Comments

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